Multiple phosphorylation events of the mitochondrial membrane protein TTM1 regulate cell death during senescence
Bibliographic record
Abstract
The role of mitochondria in programmed cell death (PCD) during animal growth and development is well documented, but much less is known for plants. We previously showed that the Arabidopsis thaliana triphosphate tunnel metalloenzyme (TTM) proteins TTM1 and TTM2 are tail-anchored proteins that localize in the mitochondrial outer membrane and participate in PCD during senescence and immunity, respectively. Here, we show that TTM1 is specifically involved in senescence induced by abscisic acid (ABA). Moreover, phosphorylation of TTM1 by multiple mitogen-activated protein (MAP) kinases regulates its function and turnover. A combination of proteomics and in vitro kinase assays revealed three major phosphorylation sites of TTM1 (Ser10, Ser437, and Ser490). Ser437, which is phosphorylated upon perception of senescence cues such as ABA and prolonged darkness, is phosphorylated by the MAP kinases MPK3 and MPK4, and Ser437 phosphorylation is essential for TTM1 function in senescence. These MPKs, together with three additional MAP kinases (MPK1, MPK7, and MPK6), also phosphorylate Ser10 and Ser490, marking TTM1 for protein turnover, which likely prevents uncontrolled cell death. Taken together, our results show that multiple MPKs regulate the function and turnover of the mitochondrial protein TTM1 during senescence-associated cell death, revealing a novel link between mitochondria and PCD.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".